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hydradx Summary (Daily)

Source: hydradx.polkaholic.io

Relay Chain: polkadot Para ID: 2034

Daily Summary for Month ending in 2023-01-31

Date Start Block End Block # Blocks # Extrinsics # Active Accounts # Passive Accounts # New Accounts # Addresses # Events # Transfers ($USD) # XCM Transfers In ($USD) # XCM Transfers Out ($USD) # XCM In # XCM Out Issues
2023-01-31 1,862,280 1,868,701 6,422 1,031 174 12 11 23,185 32,284 1,595 61 ($84,178.43) 58 ($37,585.45) 61 58
2023-01-30 1,855,826 1,862,279 6,454 757 182 12 13 23,175 28,786 1,172 46 ($22,264.42) 54 ($15,621.96) 46 54
2023-01-29 1,849,428 1,855,825 6,398 1,059 191 12 9 23,162 32,477 1,665 69 ($65,517.05) 66 ($68,034.87) 69 66
2023-01-28 1,842,947 1,849,427 6,481 1,978 272 14 40 23,154 42,735 2,856 110 ($90,881.24) 85 ($88,307.88) 110 86
2023-01-27 1,836,511 1,842,946 6,436 1,482 309 28 26 23,118 35,958 1,935 94 ($50,038.16) 67 ($58,964.01) 94 66
2023-01-26 1,830,027 1,836,510 6,484 1,983 373 29 32 23,093 41,052 2,687 160 ($128,565.77) 125 ($79,038.11) 163 128
2023-01-25 1,823,612 1,830,026 6,415 1,091 247 22 20 23,061 32,171 1,361 89 ($57,070.88) 67 ($31,517.70) 89 67
2023-01-24 1,817,161 1,823,611 6,451 1,276 351 21 23,041 34,078 1,720 86 ($57,382.10) 58 ($45,250.55) 86 58
2023-01-23 1,810,678 1,817,160 6,483 525 138 13 14 23,021 26,156 784 30 ($11,694.93) 33 ($9,829.94) 30 33
2023-01-22 1,804,171 1,810,677 6,507 265 102 5 2 23,007 23,081 398 16 ($6,411.73) 18 ($3,869.18) 16 19
2023-01-21 1,797,726 1,804,170 6,445 552 127 6 5 23,005 26,372 849 28 ($5,442.42) 36 ($92,613.78) 28 36
2023-01-20 1,791,273 1,797,725 6,453 974 188 13 11 23,000 30,565 1,175 52 ($13,276.21) 40 ($17,444.40) 52 41
2023-01-19 1,785,052 1,791,272 6,221 637 150 8 4 22,989 26,363 861 35 ($12,692.98) 21 ($24,230.93) 39 23
2023-01-18 1,778,911 1,785,051 6,141 737 167 13 11 22,985 27,833 1,107 68 ($30,994.94) 39 ($21,427.31) 68 39
2023-01-17 1,772,774 1,778,910 6,137 1,188 165 13 13 22,974 33,444 1,879 84 ($29,549.61) 44 ($55,996.00) 84 44
2023-01-16 1,766,633 1,772,773 6,141 1,316 195 15 26 22,961 34,230 1,901 68 ($20,525.98) 67 ($23,440.03) 69 67
2023-01-15 1,760,452 1,766,632 6,181 1,287 194 9 7 22,935 34,431 1,931 58 ($56,153.93) 62 ($25,257.71) 59 63
2023-01-14 1,754,262 1,760,451 6,190 1,031 199 9 12 22,928 31,146 1,449 70 ($128,147.21) 65 ($147,187.84) 70 65
2023-01-13 1,748,037 1,754,261 6,225 1,363 223 16 23 22,916 34,461 1,806 74 ($50,342.22) 69 ($49,927.03) 74 69
2023-01-12 1,741,912 1,748,036 6,125 1,261 283 10 17 22,893 33,394 1,668 89 ($87,527.80) 49 ($55,155.95) 89 49
2023-01-11 1,735,754 1,741,911 6,158 1,353 217 11 24 22,878 32,470 1,718 87 ($65,716.58) 51 ($41,278.91) 87 51
2023-01-10 1,729,610 1,735,753 6,144 1,211 238 13 20 22,856 30,939 1,553 82 ($26,140.75) 49 ($15,565.47) 82 49
2023-01-09 1,723,430 1,729,609 6,180 1,184 291 23 33 22,838 30,887 1,418 120 ($79,010.47) 78 ($29,735.94) 119 79
2023-01-08 1,717,090 1,723,429 6,340 1,307 253 17 35 22,806 33,596 1,856 135 ($48,670.37) 57 ($30,138.16) 135 58
2023-01-07 1,710,625 1,717,089 6,465 1,243 330 25 45 22,772 33,405 1,605 159 ($59,292.45) 106 ($26,991.92) 159 106
2023-01-06 1,704,118 1,710,624 6,507 4,545 995 79 156 22,735 64,501 3,949 504 ($140,276.65) 193 ($73,009.73) 505 193
2023-01-05 1,697,702 1,704,117 6,416 195 121 27 22,585 21,239 59 10 ($51,110.88) 1 ($115.70) 11 2
2023-01-04 1,691,274 1,697,701 6,428 170 60 21 11 22,559 20,903 41 4 ($11.66) 2 ($9.67) 4 2
2023-01-03 1,684,810 1,691,273 6,464 68 51 5 8 22,549 20,298 21 10 ($5.62) 1 ($5.17) 10 1
2023-01-02 1,678,543 1,684,809 6,267 56 45 26 12 22,541 19,695 29 12 ($14.72) 7 ($10.60) 11 7
2023-01-01 1,672,353 1,678,542 6,190 30 36 6 6 22,530 19,191 11 9 ($17.97) 10 ($12.47) 8 10

Sample Queries:

You can generate the above summary data using the following queries using the public dataset bigquery-public-data.crypto_polkadot in Google BigQuery:

Blocks

Schema

SELECT date(block_time) as logDT, MIN(number) startBN, MAX(number) endBN, COUNT(*) numBlocks 
 FROM `bigquery-public-data.crypto_polkadot.blocks2034`  
 where LAST_DAY(date(block_time)) = "2023-01-31" 
 group by logDT 
 order by logDT

Signed Extrinsics

Schema

SELECT date(block_time) as logDT, 
COUNT(*) numSignedExtrinsics 
FROM `bigquery-public-data.crypto_polkadot.extrinsics2034`  
where signed and LAST_DAY(date(block_time)) = "2023-01-31" 
group by logDT 
order by logDT

Active Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numActiveAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountsactive2034` 
 where LAST_DAY(date(ts)) = "2023-01-31" 
 group by logDT 
 order by logDT

Passive Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numPassiveAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountspassive2034` 
 where LAST_DAY(date(ts)) = "2023-01-31" 
 group by logDT 
 order by logDT

New Accounts

Schema

SELECT date(ts) as logDT, 
 COUNT(*) numNewAccounts 
 FROM `bigquery-public-data.crypto_polkadot.accountsnew2034` 
 where LAST_DAY(date(ts)) = "2023-01-31" 
 group by logDT
 order by logDT

Addresses with Balances

Schema

SELECT date(ts) as logDT,
 COUNT(distinct address_pubkey) numAddress 
 FROM `bigquery-public-data.crypto_polkadot.balances2034` 
 where LAST_DAY(date(ts)) = "2023-01-31" 
 group by logDT 
 order by logDT

Events

Schema

SELECT date(block_time) as logDT, 
 COUNT(*) numEvents 
 FROM `bigquery-public-data.crypto_polkadot.events2034` 
 where LAST_DAY(date(block_time)) = "2023-01-31" 
 group by logDT 
 order by logDT

Transfers:

Schema

SELECT date(block_time) as logDT, 
 COUNT(*) numEvents 
 FROM `bigquery-public-data.crypto_polkadot.transfers2034` 
 where LAST_DAY(date(block_time)) = "2023-01-31" 
 group by logDT 
 order by logDT

XCM Transfers In:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMTransfersOut 
 FROM `bigquery-public-data.crypto_polkadot.xcmtransfers` 
 where destination_para_id = 2034 and LAST_DAY(date(origination_ts)) = "2023-01-31" 
 group by logDT order by logDT

XCM Transfers Out:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMTransfersIn 
 FROM `bigquery-public-data.crypto_polkadot.xcmtransfers` 
 where origination_para_id = 2034 and LAST_DAY(date(origination_ts)) = "2023-01-31" 
 group by logDT 
order by logDT

XCM Messages In:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMMessagesOut 
 FROM `bigquery-public-data.crypto_polkadot.xcm` 
 where destination_para_id = 2034 and LAST_DAY(date(origination_ts)) = "2023-01-31" 
 group by logDT order by logDT

XCM Messages Out:

Schema

SELECT date(origination_ts) as logDT, 
 COUNT(*) numXCMMessagesIn 
 FROM `bigquery-public-data.crypto_polkadot.xcm` 
 where origination_para_id = 2034 and LAST_DAY(date(origination_ts)) = "2023-01-31" 
 group by logDT 
order by logDT

Report source: https://cdn.polkaholic.io/substrate-etl/polkadot/2034.json | See Definitions for details